Computational Physics - Scaling

In summary, you should "scale the problem carefully by setting the units such that the non-test masses have a mass of 1 and G, the universal gravitation constant, equals 1."
  • #1
secret2
37
0
Hi all,

I am not sure if I'm posting on the right place. I am currently working on a computational project. It's about simulating a system with two non-test masses and a bunch of test masses. The instruction sheet says that we should "scale the problem carefully by setting the units such that the non-test masses have a mass of 1 and G, the universal gravitation constant, equals 1."

The lecturer did a bad job explaining what scaling really is, and I am not sure what exactly I should do concerning scaling here. Could someone give me a hand?
 
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  • #2
What you write doesn't make a whole lot of sense. If you had one mass, you could certainly choose ITS mass as the "unit of mass" and so it would have mass 1- you would then "scale" by dividing all other masses by the "unit" mass.

However, if you have "two non-test masses", unless they are both the same mass, obviously you can't have both with mass 1.


Once you have selected a given unit of mass, setting G (I presume you don't mean "g") equal to 1 is a matter of choosing an appropriate distance measure.
 
  • #3
HallsofIvy,

Thank you for your help, I have been desperately looking for reply.

First of all, you are right that the two non-test masses have equal masses. I am not sure why you commented that "obviously you can't have both with mass 1".

And after having selected a given unit of mass, setting G equal to 1 is "a matter of choosing an appropriate distance measure" as you mentioned. To be explicit, I have two questions:

1. Do I need to 'scale' both distance and time?
2. Is it true that I have to divide distance by the sqrt of G in order to scale it?

Many thanks!
 
  • #4
You said you had two "non-test masses". You didn't say they were the same. What exactly IS a "non-test mass"??
G has units of [itex]\frac{m^3}{(kg)(sec^2)} Yes, you will need to scale all of them. The point is choosing each of those so that G is 1.
 
  • #5
When I said 'test mass' I mean that they will not exert any gravitational attraction onto the other test/non-test masses (they of course REACT to the attraction of the non-test masses). So you can say that there are only two sources of gravitational attraction.

Cheers
 

Related to Computational Physics - Scaling

1. What is computational physics and why is scaling important in this field?

Computational physics is the use of computer simulations and mathematical models to study and solve complex physical problems. Scaling is important in this field because it allows us to understand how a system behaves as its size or parameters change. This is crucial in understanding the behavior of complex systems and making accurate predictions.

2. How is scaling different from dimensional analysis?

Scaling and dimensional analysis are related concepts, but they have different purposes. Scaling focuses on how the behavior of a system changes as its size or parameters change, while dimensional analysis looks at the relationship between different physical quantities in a system.

3. What are the different types of scaling in computational physics?

There are three main types of scaling in computational physics: spatial scaling, temporal scaling, and parameter scaling. Spatial scaling involves changing the size or dimensions of a system, temporal scaling involves changing the time scale of a system, and parameter scaling involves changing the values of parameters within a system.

4. How is scaling used in simulations and modeling?

Scaling is used in simulations and modeling to understand how a system behaves at different scales. By varying the size or parameters of a system, we can simulate and model how it will behave in different scenarios and make predictions about its behavior in the real world.

5. What are some challenges in scaling in computational physics?

One of the main challenges in scaling in computational physics is accurately representing real-world systems in simulations. This requires careful consideration of the relevant physical laws and parameters, as well as the limitations of computational power. Another challenge is identifying the appropriate scaling laws for a given system, as different systems may exhibit different scaling behaviors.

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